Welcome back to the weekly Work Management Roundup, where we collect the week's best reads in work, business management, and productivity to inspire you to work smarter. This week, we open with three articles that tackle why we're not performing at our best: we lack sleep, we don't schedule time for deep work, and we're addicted to multitasking. Read on!
Employees Don't Get Enough Sleep, and It's Your Fault (Entrepreneur): The studies prove modern workers are sleep deprived due to work stress. And where's that stress stemming from? Missing info, unclear leadership, lack of collaboration, and ever-changing deadlines. It's quite real, and it's affecting our health.
Talk to Your Boss About Deep Work (Cal Newport's Study Hacks): If your office culture expects you to respond ASAP to every instant message and email, then you're probably not getting much deep work done. Here's how to tell your boss you want to set apart some distraction-free time everyday dedicated to creative problem solving, deep thinking, and deep work.
Addicted to Multitasking: The Scientific Reasons You Can’t Stop Juggling Work (Wrike): Many people know that focusing on one task at a time leads to much better results, yet we still find ourselves multitasking in an attempt to check items off our to-do lists twice as fast. Why is multitasking so seductive? And what can we do to make our propensity to indulge distractions work for us, instead of against us?
How To Survive Working On An Underperforming Team (Fast Company): Each team has a unique dynamic, but even if the team performs poorly, there are three ways to maximize the effectiveness of your team. These involve: sharing a mission, finding everyone's roles, and engaging a mentor.
How Big Data Creates False Confidence (Nautilus): The big problem with big data? The temptation to think that studies relying on big data couldn’t be wrong. Because there's just so much data to back it up, right? Unfortunately the bigness of the data can imbue results with a false sense of certainty. Many of the results are probably bogus—and the reasons why should give us pause about any research that blindly trusts big data.